Maternal health expert feedback on the attributes of a predictive analytics tool to improve pregnancy-related cardiovascular and mental health outcomes in the United States

ABSTRACT

Identify pregnancy-related challenges and opportunities to improve maternal health care in the United States and understand the potential role of predictive analytics tool(s) in bridging the existing gaps, specifically, in CVD (cardiovascular disease) and depression. Experts in maternal health care, research, patient advocacy, CVD, psychiatry, and technology were interviewed during February and March of 2020. Additionally, published literature was reviewed to assess existing data, insights, and best practices that might help develop effective predictive analytics tool(s). The majority (78%) of the 18 experts interviewed were women. The feedback revealed several insights, including multiple barriers to diagnosis and treatment of pregnancy-related CVD and depression. In experts’ collective opinion, predictive analytics could play an important role in maternal health care and in limiting pregnancy-related CVD and depression, but it must be grounded in quality data and integrate with existing health management systems. A holistic approach to maternal health that factors in racial-ethnic, regional, and socioeconomic disparities is needed that starts with preconception counseling and continues through 1 year postpartum. Predictive analytics tool(s) that are based on diverse and high-quality data could bridge some of the existing gaps in maternal health care and potentially help limit pregnancy-related CVD and depression.

KEYWORDS:

• Women’s health
• pregnancy-related death
• perinatal cardiovascular disease
• postpartum depression
• digital technology

Acknowledgments

Authors thank Saroj Sedalia, Vice President, Rabin Martin, New York, NY, for her role in conducting some expert interviews and in data acquisition, and Joy Marini, Senior Director, Health of Women, Johnson & Johnson, for her insights into the framework used to interview experts for this study. Writing assistance was provided by Narender Dhingra, MBBS, PhD, CMPP, of System One, and funded by Janssen Global Services, LLC.

Disclosure statement

SVS and RRJ are employees of Johnson & Johnson and own stock and/or stock options. MM is an employee of Rabin Martin, the firm that conducted the expert interviews.

Data Availability Statement

All data generated or analyzed during this study are represented in this published article.

Additional information

Funding

This work was supported by Johnson & Johnson.